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AI security incident: engram: HTTP server CORS wildcard + auth-off-by-default enables CSRF graph exfiltrati...

Incident date: April 22, 2026 | Published: April 22, 2026 | Source: GitHub Security Advisory | Classification confidence: 45%

This incident is part of the public archive and includes explicit AI-related signals from the cited source material. Review methodology.

engram: HTTP server CORS wildcard + auth-off-by-default enables CSRF graph exfiltration and persistent indirect prompt injection Summary The local HTTP server started by engram server (binding 127.0.0.1:7337 by default) was exposed to any browser origin with no authentication unless ENGRAM API...

Why This Is AI-Related

This page is treated as AI-specific because the source material references prompt injection, which places the issue inside an AI workflow, model, assistant, or supporting dependency rather than a generic software bulletin.

  • prompt injection

Affected Workflow

LLM prompts, agent workflows, retrieval layers, and connected tools should be reviewed first.

Likely Attack Path

Untrusted prompts or tool instructions can override intended guardrails, then trigger data access or unsafe downstream actions.

Impact

The weakness can let untrusted prompts or tool instructions bypass intended guardrails and trigger unsafe downstream actions or data access. Severity HIGH. Classification confidence 45%. Source channel GHSA.

Detection And Triage Signals

  • Unexpected tool invocation chains after user prompts
  • Prompt logs that include instruction override patterns or policy bypass text
  • Retrieval or plugin calls that expose sensitive internal context

Recommended Response

  • Review prompt templates, tool-invocation rules, and system instructions for the affected workflow.
  • Restrict sensitive tools, retrieval scopes, and outbound actions until guardrails are validated.
  • Search logs for prompt override attempts, unusual tool chains, and sensitive data exposure after user input.

Compliance And Business Impact

Prompt-layer weaknesses can expose regulated data, create unsafe actions, and weaken audit evidence around AI control boundaries.

Sources

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